The tool provides customised solutions based on circumstantial requirements, allowing security teams to efficiently manage unique security or safety needs. It works effectively with detecting distinct objects. Some examples of objects it can be trained to detect are boxes posing a hazard on a shop floor, cones obstructing roads, or signs blocking corridors.

The flexibility of the machine-learning-based detection also creates opportunities for safety and security teams to reinforce other measures, such as access control. For example, Wisedetector can learn to recognise open or closed doors and provide a visual alert that improves access control.

Training the Wisedetector model is achieved through the Device Manager and users do not need deep technical knowledge to get started. This makes it relatively easy to set up and further expands the possibilities of video analytics. Users simply collect images of a target object and the machine-learning model learns to recognise it. When the trained Wisedetector model is applied, it can then use existing video analytics applications on the camera to trigger live events.

Pread Um (Suk Bong), Director of Product and Marketing at Hanwha Vision said, “Wisedetector is another tool in Hanwha Vision’s offering that expands the use of video analytics. We are committed to helping our customers use video analytics for the many benefits it brings to security, operations, and individual safety. Wisedetector is one of the ways we are achieving that, along with our edge AI devices and deep-learning algorithms that only continue to evolve and advance.”